TY - JOUR AU - Xavier Soria AU - Angel Sappa AU - Riad I. Hammoud PY - 2018// TI - Wide-Band Color Imagery Restoration for RGB-NIR Single Sensor Images T2 - SENS JO - Sensors SP - 2059 VL - 18 IS - 7 KW - RGB-NIR sensor KW - multispectral imaging KW - deep learning KW - CNNs N2 - Multi-spectral RGB-NIR sensors have become ubiquitous in recent years. These sensors allow the visible and near-infrared spectral bands of a given scene to be captured at the same time. With such cameras, the acquired imagery has a compromised RGB color representation due to near-infrared bands (700–1100 nm) cross-talking with the visible bands (400–700 nm).This paper proposes two deep learning-based architectures to recover the full RGB color images, thus removing the NIR information from the visible bands. The proposed approaches directly restore the high-resolution RGB image by means of convolutional neural networks. They are evaluated with several outdoor images; both architectures reach a similar performance when evaluated in differentscenarios and using different similarity metrics. Both of them improve the state of the art approaches. UR - https://doi.org/10.3390/s18072059 L1 - http://refbase.cvc.uab.es/files/SSH2018.pdf UR - http://dx.doi.org/10.3390/s18072059 N1 - ADAS; MSIAU; 600.086; 600.130; 600.122; 600.118 ID - Xavier Soria2018 ER -